Opeyemi Joseph AjayiVerified StackedHQ member

AI-Powered Lead Intake & Qualification System Built for: Week 1 Challenge, Tools: n8n, OpenAI, Google Sheets, Gmail The Problem: Most agencies handle inbound leads manually a form comes in, someone reads it, figures out what's needed, logs it into a spreadsheet, and notifies the right person. This works at low volume, but as enquiries scale, response times slip and qualified leads go cold. The Solution: I built an automated pipeline that takes a lead from form submission to a prioritized inbox notification in under 60 seconds. A prospect submits a Web form, n8n triggers instantly via webhook,

Instead of having staff read through long customer emails or contact form submissions and in the process missing mail or form submission, AI analyzes the inquiry and extracts only what matters. The workflow: - Accepts inquiries from both Gmail and a website contact form. - Normalizes the data into a single format regardless of the source. - Uses OpenAI to determine whether the message is actually a customer inquiry. - Stops the workflow automatically if it isn't a genuine customer request. - Extracts key information including: - Service requested - Required action - Preferred appointment dat

Every consultant knows this feeling. You're in the middle of focused work when an email comes in asking for your proposal, capability deck, or pricing. You stop, search Google Drive, find the right file, write a reply, attach the document, and save or send it. It's not hard. It's just repetitive. So for this week's challenge from @TheStackHQ, I built an AI workflow that takes care of almost everything for me. Here's what it does: • Monitors incoming Gmail messages. • Uses AI to determine whether the email is requesting documents. • Identifies exactly which document was requested. • Search

Today, I'll be presenting Automated Trip Reminder System, built using n8n to automate customer communication for travel businesses. Many travel companies still send reminders manually. As bookings increase, this becomes time-consuming and can lead to missed reminders, duplicate messages, and poor customer experience. This workflow solves that problem by automating the entire process. The workflow begins with a Schedule Trigger, which runs every morning automatically. It then uses the Google Sheets node to read customer trip records. Next, a Code node evaluates each trip and determines whethe

I built two lightweight AI automations to take repetitive admin work off an ops team living in Gmail, Sheets, and Docs all day. Approach: The client's team needed reliability over cleverness, so I focused on predictable behavior first every step either completes cleanly or clearly flags itself for human review, nothing silently fails or duplicates. Tools used: n8n for orchestration, the OpenAI for summarization and drafting, and native Gmail, Google Sheets, and Google Docs integrations, with Slack for notifications. What it does: Flow 1 watches Gmail for a specific label, has AI summarize t

I automate the entire lead intake process so every lead is handled consistently and no potential customer is missed. Leads can enter through a website form or email. Both sources are normalized into the same data structure using Prepare nodes, ensuring every lead follows the same process regardless of origin. The standardized data is sent to OpenAI, which extracts structured information, summarizes the enquiry, and classifies the lead as Hot, Warm, or Cold based on predefined business rules. Structured output ensures reliable downstream processing and reduces parsing errors. Every qualified

This workflow automates the first stage of customer support while keeping a human in control of every customer-facing response. When a new support email arrives in Gmail, the AI Agent reads the message and uses the company's knowledge base to determine whether the question can be answered from documented information. The OpenAI model analyzes the request, while the knowledge base provides the source for factual answers. The Structured Output Parser ensures the AI returns consistent information, including the customer's name, email, category, confidence, summary, draft response, and escalatio

This n8n workflow solves a common bottleneck at marketing agencies: manual lead triage. Previously, every web-form submission had to be read, categorised, and routed to the right rep by hand — a delay that let hot leads go cold before anyone responded. The workflow starts with a Webhook that captures incoming form submissions and cleans the raw data. An AI Lead Analyser (powered by an OpenAI Chat Model with a Structured Output Parser) scores each lead's seriousness and tags the project type, returning consistent, structured JSON instead of free text. A Switch node routes leads by temperature

Dental practices lose patients every day to unanswered calls. Front desk staff are often busy in-office, and a missed call with no follow-up usually means a lost booking. I built an automation that solves this without adding any staff workload. How it works: A webhook captures every missed call the moment it happens. The system checks the caller against existing patient records in Google Sheets, then instantly sends a personalized SMS response via the Telerivet API. For calls needing more nuanced handling, an AI model generates a context-aware reply instead of a generic template. Every call a

This n8n workflow automates the entire product photo pipeline from raw upload to store-ready image with zero manual editing. Fetch: Every minute, the workflow checks the Dropbox Raw folder for new uploads, filters for image files only, moves matched files to a Processing folder, and downloads the original for editing. Process: Each image is converted to PNG and rotated for consistency, then passed to an AI model that standardizes the look cleaning up the background and applying the brand's product style. A Quality Check step then verifies the result: if it passes, it's resized and formatted

A freelance designer kept sending generic copy-paste outreach or spending forever writing each message from scratch so outreach mostly didn't happen. I built a workflow that turns a short prospect note into a ready-to-review draft: A Google Sheets trigger fires when a new prospect row is added. An IF node checks the "To Send" column is empty, so existing drafts never get overwritten. An OpenAI node reads the business name, type, location, website, and note, then writes a short, personal first message grounded in real details not a template. On success, the draft is cleaned of stray quotes and

I built an AI-powered website chat assistant for a fitness gym (FitCore) using n8n, OpenAI, and Google Sheets, triggered by an embedded chat widget via webhook. The assistant answers visitor questions hours, membership pricing, class schedules, facilities strictly from a connected knowledge base document, refusing to guess or fabricate details it doesn't have. It conversationally collects the visitor's name, phone, email, and reason for reaching out over the course of the chat, rather than front-loading a form, and it distinguishes between "all lead data collected" and "conversation actually

I built an n8n workflow that fixes the "signups go quiet" problem for my sample SaaS, Flowdesk. It has two parts. Welcome flow: A Signup webhook (POST, secured with Header Auth) receives new trial signups from the landing page. A Config node maps the incoming fields, then an Airtable node creates a record in a "Database for Mail" base (Name, Email, Date, Mail Sent, Reminder Sent). Gmail sends a personalized welcome email pointing the user to their first action ("Start your first project"), Airtable is updated to mark Mail Sent, and the webhook responds so the frontend can confirm signup. Rem

I built an AI-powered freelance job screening workflow in n8n to help an agency find relevant opportunities without manually scrolling through job boards. The workflow pulls new job postings from Freelancer on a schedule. A Code node performs an initial filter using relevant AI and automation keywords while removing obvious unrelated roles such as software development, accounting, QA, sales, and administrative jobs. The remaining jobs are passed to an AI model along with the agency's profile. The AI evaluates the actual job requirements against the agency's services and scores each posting f

I built an AI-powered WhatsApp ordering automation for AJO Bakery using n8n, OpenAI GPT-5 mini, Google Sheets, and Google Docs. The goal is to reduce the manual work involved in receiving, recording, and managing bakery orders through WhatsApp. When a customer sends a message, the workflow identifies the message type and uses an AI agent to understand the customer's request. It can collect order details, ask follow-up questions when information is missing, and request confirmation before processing an order. Once confirmed, the workflow generates a unique order ID, calculates the order subt